All of the patents, patent applications, technical papers and other references referenced above and below are incorporated herein by reference in their entirety.
The invention relates to several different areas and a discussion of some particular areas of interest follows.
1. Pattern Recognition
Pattern recognition techniques, such as artificial neural networks are finding increased application in solving a variety of problems such as optical character recognition, face recognition, voice recognition, and military target identification. In the automotive industry in particular, pattern recognition techniques have now been applied to identify various objects within the passenger compartment of the vehicle, such as a rear facing child seat, as well as to identify threatening objects with respect to the vehicle, such as an approaching vehicle about to impact the side of the vehicle. See, for example, U.S. Pat. Nos. 05,829,782, 06,343,810 and U.S. RE 37,260.
Pattern recognition techniques have also been applied to sense automobile crashes for the purpose of determining whether or not to deploy an airbag or other passive restraint, or to tighten the seatbelts, cutoff the fuel system, or unlock the doors after the crash (see, for example, U.S. Pat. No. 05,684,701). In the past, pattern recognition techniques were not applied to forecast the severity of automobile crashes for the purpose of controlling the flow of gas into and/or out of an airbag to tailor the airbag inflation characteristics and/or to control seatbelt retractors, pretensioners and energy dissipaters to match the crash severity. Furthermore, such techniques were also not used to control the flow of gas into and/or out of an airbag to tailor the airbag inflation characteristics to the size, position and/or relative velocity of the occupant or other factors such as seatbelt usage, seat and seat back positions, headrest position, vehicle velocity, etc.
Neural networks are constructed of processing elements known as neurons that are interconnected using information channels often called interconnects organized into different layers. Each neuron can have multiple inputs but only one output. Each output however is usually connected to all other neurons in the next layer in the direction of processing. The neurons in the first layer operate collectively on the input data as described in more detail below. Neural networks learn by extracting relational information from the data and the desired output. Neural networks have been applied to a wide variety of pattern recognition problems including automobile occupant sensing, speech recognition, optical character recognition, and handwriting analysis.
2. Electronic Crash Sensors
Electronic crash sensors currently used in sensing frontal impacts typically include accelerometers mounted in the passenger compartment that detect and measure vehicle accelerations during the crash. The accelerometer produces an analog signal proportional to the acceleration experienced by the accelerometer and hence the vehicle on which it is mounted. An analog to digital converter (ADC) transforms this analog signal into a digital time series. Crash sensor designers study this digital acceleration data and derive therefrom computer algorithms which determine whether the acceleration data from a particular crash event warrants deployment of the airbag. This is usually a trial and error process wherein the engineer or crash sensor designer observes data from crashes where the airbag is desired and when it is not needed, and other events where the airbag is not needed. Finally, the engineer or crash sensor designer settles on the “rules” for controlling deployment of the airbag which are programmed into an algorithm which seem to satisfy the requirements of the crash library, i.e., the crash data accumulated from numerous crashes and other events and the associated desired restraint reaction. The resulting algorithm is not universal and most such engineers or crash sensor designers will answer in the negative when asked whether their algorithm will work for all vehicles. Such an algorithm also merely determines that the airbag should or should not be triggered. Prior to the current assignee's activities, no attempt is believed to have been made to ascertain or forecast the eventual severity of the crash or, more specifically, to forecast the velocity change versus time of the passenger compartment from the previous acceleration data obtained from the accelerometer.
Several papers as listed below have been published pointing out some of the problems and limitations of electronic crash sensors mounted out of the crush zone of the vehicle, usually in a protected location in the passenger compartment of the vehicle. These sensors are frequently called single point crash sensors. Technical papers which discuss the limitations of current single point sensors along with discussions of the theory of crash sensing are listed below. The only use of electronic sensors at the time of the filing of the current assignee's earliest parent patent application to (U.S. Pat. No. 05,842,716 filed Sep. 16, 1993) was for non-crush zone sensing of frontal crashes. Patent U.S. Pat. No. 03,701,903 shows crash sensors mounted near the front of the vehicle but it also points out that they are used “. . . in response to changes in the vehicle's velocity” as opposed to the velocity change to a portion of the vehicle that undergoes crushing. Engineers involved in crash testing at that time were aware that in a crash test, it was common to lose one or more of the front crush zone mounted accelerometers and thus the prevailing wisdom was that the crush zone was not a place to position electronic sensors.
These papers demonstrate, among other things, that there is no known theory that allows an engineer to develop an algorithm for sensing crashes and selectively deploying the airbag except when the sensor is located in the crush zone of the vehicle. These papers show that, in general, there is insufficient information within the acceleration signal measured in the passenger compartment to sense all crashes. Another conclusion suggested by these technical papers is that if an algorithm can be found which works for one vehicle, it will also work for all vehicles since it is possible to create any crash pulse measured in one vehicle, in any vehicle. In this regard, reference is made in particular to SAE paper 920124 discussed below.
In spite of the problems associated with finding the optimum crash sensor algorithm, many vehicles on the road today have electronic single point crash sensors. Some of the problems associated with single point sensors have the result that an out-of-position occupant who is sufficiently close to the airbag at the time of deployment will likely be injured or killed by the deployment itself. Fortunately, systems are now being developed, and are in limited production, that monitor the location of occupants within the vehicle and can suppress deployment of the airbag if the occupant is more likely to be injured by the deployment than by the accident. However, these systems are not believed to currently provide the information necessary for the control of airbag systems, or the combination of seatbelt and airbag systems, which have the capability of varying the flow of gas into and/or out of the airbag and thus to tailor the airbag to the size and/or weight of the occupant (and/or possibly another morphological characteristic of the occupant), as well as to the position, velocity and/or seatbelt use of the occupant. More particularly, no such system existed, prior to the conception by the current assignee's personnel, which uses pattern recognition techniques to match the airbag deployment and/or gas discharge from the airbag to the severity of the crash and/or the size, weight, position, velocity and/or seatbelt use of an occupant.
Once any crash sensor has determined that an airbag should be deployed, the system can perform other functions such as tightening the seatbelts for those vehicles which have seatbelt retractor systems, cutting off of the fuel system to prevent fuel spillage during or after the crash, and unlocking the doors after the crash to make it easier for the occupant(s) to escape.
3. Crash Severity Prediction
When a crash commences, the vehicle starts decelerating and an accelerometer located in the passenger compartment, and/or one or more satellite or crush zone mounted accelerometers, begins sensing this deceleration and produces one or more electronic signals that vary over time in proportion to the magnitude of the deceleration. These signals contain information as to the type of the crash which can be used to identify the crash. A crash into a pole gives a different signal than a crash into a rigid barrier, for example, even during the early portion of the crash before the airbag triggering decision has been made. A neural network pattern recognition system can be trained to recognize and identify the crash type from the early signal from a passenger compartment mounted sensor, for example, and further to forecast ahead the velocity change versus time of the crash. Naturally, if the neural network also has information from satellite or crush zone mounted sensors, the accuracy of the forecast is significantly improved. Once this forecast is made, the severity and timing of the crash can be predicted. Thus, for a rigid barrier impact, an estimate of the eventual velocity change of the crash can be made and the amount of gas needed in the airbag to cushion an occupant as well as the time available to direct that amount of gas into the airbag can be determined and used to control the airbag inflation.
Another example isa crash into a highway energy absorbing crash cushion. In this case, the neural-network-based sensor determines that this is a very slow crash and causes the airbag to inflate more slowly thereby reducing the incidence of collateral injuries such as broken arms and eye lacerations.
In both of these cases, the entire decision making process takes place before the airbag deployment is initiated. In another situation where a soft crash is preceded by a hard crash, such as might happen if a pole were in front of a barrier, the neural network system would first identify the soft pole crash and begin slowly inflating the airbag. However, once the barrier impact begins, the system would recognize that the crash type has changed and recalculate the amount and timing of the introduction of gas into the airbag and send appropriate commands to the inflation control system of the airbag to possibly vary the introduction of gas into the airbag. Again, if crush zone mounted sensors are present, the accuracy of the crash severity is greatly enhanced.
The use of pattern recognition techniques in crash sensors has another significant advantage in that it can share the same pattern recognition hardware and software with other systems in the vehicle. Pattern recognition techniques have proven to be effective in solving other problems related to airbag passive restraints. In particular, the identification of a rear-facing child seat located on the front passenger seat, so that the deployment of the airbag can be suppressed, has been demonstrated. Also, the use of pattern recognition techniques for the classification of vehicles about to impact the subject vehicle, particularly the side, for use in anticipatory crash sensing shows great promise. Both of these pattern recognition systems, as well as others under development, can use the same computer system as the crash sensor and prediction system of this invention. Moreover, both of these systems preferably will need to interact with, and should be part of, the diagnostic module used for frontal impacts. It would be desirable for cost and reliability considerations, therefore, for all such systems to use the same computer system or at least be located in the same electronic module. This is particularly desirable since computers designed specially for solving pattern recognition problems, such as neural-computers, are now available and can be integrated into a custom application specific integrated circuit (ASIC).
4. Crush Zone Mounted Sensors
In Society of Automotive Engineers (SAE) Paper No. 930650 entitled “A Complete Frontal Crash Sensor System (8), the authors conclude that airbag crash sensors mounted in the crush zone are necessary for the proper sensing of airbag-required frontal crashes. They also conclude that such sensors should sense crashes to all portions of the front of the vehicle and that sensors which sense the crush of the vehicle are preferred. The theory of crush sensing is presented in the above-referenced U.S. patents and patent applications and particularly in reference (6).
The tape switch and rod-in-tube crush sensors described in the above-referenced U.S. patents and patent applications have performed successfully on various staged vehicle frontal crashes into barriers and poles. These sensors are generally not sufficient for sensing side impacts as discussed in reference (11), however, they can be successful when used in conjunction with a passenger compartment mounted electronic sensor or as a safing sensor. Similarly, they are also being considered when a deployable device, such as an airbag, is used for rear impacts. Newer elongate crush zone mounted sensors are being developed that continuously measure the relative displacement, velocity change or acceleration of a particular location in the crush zone and therefore can give much improved information about the locating of an impact and the characteristics of the crash such as its severity.
Sensors have been widely used in the crush zone to sense and initiate deployment of an air bag passive restraint system. These sensors include an air damped ball-in-tube sensor such as disclosed in U.S. Pat. Nos. 03,974,350, 04,198,864, 04,284,863, 04,329,549 and 04,573,706 (all in the name of Breed) and a spring mass sensor such as disclosed in U.S. Pat. Nos. 04,116,132 and 04,167,276 (both in the name of Bell). In addition, a passenger compartment-mounted electronic sensor is now the most common sensor in airbag systems. Each of these sensors has particular advantages and shortcomings that are discussed in detail in U.S. Pat. No. 04,995,639.
The use of tape or ribbon switch technology as a crush switch was also disclosed in the '639 patent. Further research has shown that an improvement of this particular implementation has significant advantages over some of the other implementations since the switch can be easily made long and narrow and it can be made to respond to bending. In the first case, it can be designed to cover a significant distance across the vehicle that increases the probability that it will be struck by crushed material or bent as the crush zone propagates rearward in the vehicle during a crash. In the second case, it can be made small and located to sense the fact that one part of the vehicle has moved relative to some other part or that the structure on which the sensor is mounted has deformed.
Other crush zone mounted crash sensors including crush switch designs where the width and height dimensions are comparable, must either be large and thus heavy, expensive and difficult to mount, or there is a possibility that the randomly shaped crushed material which forms the boundary of the crush zone will bridge the sensor resulting in late triggering. This crushed material frequently contains holes, wrinkles or folds or portions that may even be displaced or torn out during the crash with the result that it is difficult to guarantee that a particular small area where the sensor is mounted will be struck early in the crash.
A significant improvement results, therefore, if the sensor can stretch across more of the vehicle or if it can determine that there has been relative motion or deformation of a portion of the vehicle on which the sensor is mounted. The improved sensors described herein are small in height and thickness but can extend to whatever length is necessary to achieve a high probability of a sensor triggering on time in a crash.
It has been found that conventional designs of tape or ribbon switches have the drawback that the force required to close the switch is very small compared with the forces which are normally present in automobile crashes. During routine maintenance of the vehicle, the normal tape switch may be damaged or otherwise made to close and remain closed, with the result that later, when the vehicle encounters a pot hole or other shock sufficient to cause the arming sensor to close, an inadvertent air bag deployment can result. Similarly, if the tape switch is mounted on the front of the radiator support, which is a preferred mounting locating for crush zone sensors, hail, heavy rain, stones or other debris from the road might impact the tape switch and cause a momentary closure or damage it. If this happens when the vehicle experiences a shock sufficient to cause the arming sensor to close, an inadvertent air bag deployment might also occur. The force typically required to close a tape switch is less than one pound whereas tens of thousands of pounds are required to stop a vehicle in a crash and local forces greatly in excess of 20 pounds are available to actuate a sensor during a crash.
The present invention seeks to eliminate these drawbacks through the use of a tape switch, rod-in-tube or coaxial cable design that requires either a large force to actuate or a bending of the device due to structural deformation as explained below.
In 1992, the current assignee published reference (5) where the authors demonstrate that there is insufficient information in the non-crush zone of the vehicle to permit a decision to be made to deploy an airbag in time for many crashes. The crash sensors described herein and in the patents and patent applications referenced above, provide an apparatus and method for determining that the crush zone of the automobile has undergone a particular velocity change. This information can be used by itself to make the airbag deployment decision. As airbag systems become more sophisticated, however, the fact that the vehicle has undergone a velocity change in the crush zone can be used in conjunction with an electronic sensor mounted in the passenger compartment to not only determine that the airbag should be deployed but an assessment of the severity of the crash can be made. In this case, the front crush zone mounted sensor of the type disclosed herein can be used as an input to an electronic algorithm and thereby permit a deployment strategy based on the estimated severity of the accident. Although the sensors described herein are one preferred approach of providing this capability, the sensors disclosed in the above referenced patents would also be suitable. Alternately, in some cases, sensors of another design can fulfill this function. Such sensors might be based on the electromechanical technologies such as the ball-in-tube sensor described in U.S. Pat. No. 04,900,880 and now electronic sensors can be used as crush zone mounted sensors for this purpose as is the object of the instant invention.
For the purposes herein, the crush zone is defined as that part of the vehicle which crushes or deforms during a particular crash. This is a different definition from that used elsewhere and in particular in the above-referenced technical papers. Also for the purposes herein, the terminology Crush Sensing Zone, or CSZ, will be used to designate that portion of the vehicle which is deformed or crushed during a crash at the sensor-required trigger time. The sensor-required trigger time is considered the latest time that a crash sensor can trigger for there to be sufficient time to deploy the airbag. This is determined by the airbag system designers and is a given parameter to the sensor designer for a particular crash. Naturally, there will be a different sensor-required trigger time for each crash, however, it has been found, as reported in the above references, that the CSZ is remarkably constant for all crashes of the same type.
For example, the CSZ is nearly the same for all frontal barrier crashes regardless of the velocity of the crash. The same is true for 30 degree angle barrier crashes although the CSZ is different here than for frontal barrier crashes. Remarkably, and unexpectedly, it has also been found that when all frontal crashes at all different velocities are taken into account, the CSZ rearmost boundary becomes an approximate three dimensional surface lying mostly within the engine compartment of the vehicle, typically about ten to twelve inches behind the bumper at the center, and extending backward when crashes outside of the rails are considered. Finally, if a sensor is placed on this CSZ surface so that it is higher than the bumper level on the sides of the vehicle and lower in the vehicle center, as shown in FIG. 7 herein, it will do a remarkable job at discriminating between airbag required and non-deployment crashes and still trigger by the sensor-required trigger time and before other sensors of comparable sensitivity. Naturally, this system is not perfect, however, it has been shown to do a better job than any other sensor system now in use.
It was this discovery which provided a basis for the subject matter described in U.S. Pat. No. 04,995,639 and then to the rod-in-tube sensor described in U.S. Pat. No. 05,441,301. During the process of implementing the rod-in-tube sensor, it was found that the same theory applies to rear impacts and that rod-in-tube sensors also have applicability to side impact sensing, although the theory is different.
In U.S. Pat. No. 05,694,320 (Breed), the theory of sensing rear impacts is presented and it is concluded that an anticipatory sensing system is preferred. This is because many people suffer whiplash injuries at rather low velocity impacts and if an inflatable restraint is used, the repair cost may be significant. To protect most people from whiplash injuries in rear impacts, therefore, a resetable system is preferred. The argument on the other side is that if the headrest is properly positioned, it will take care of all of the low velocity impacts and, therefore, an airbag can be used and reserved for the high velocity impacts where a crush sensing crash sensor would be used. The rod-in-tube sensor disclosed herein is, therefore, ideal for use with a deployable headrest mounted airbag for the same reasons that it is a good sensor for sensing frontal impacts. Since the rear of a vehicle typically has about one third of the stiffness of the vehicle front, electronic sensors will have even a tougher time discriminating between trigger and non-trigger cases for rear impacts. As disclosed in references 5 and 9 above, it is the soft crashes that are the most difficult for electronic sensors to sense in time.
Crush sensing crash sensors are not ideal for sensing side impacts alone, although at least one Volvo side impact system uses such a sensing system. This is because the sensing time is so short that there is virtually no crush (about two inches) at the time that the airbag must be deployed. Since there is very little signal out of the crush zone where electronic sensors are mounted, electronic sensors alone are not able to discriminate airbag required crashes from other crashes not requiring airbag deployment. The combination of the two sensors, on the other hand, can be used to provide a reliable determination. The crush sensor determines that there has been two inches of crush and the electronic sensor determines that the acceleration signal at that time is consistent with an airbag-required crash occurring. Thus, although they cannot be reliably used alone as a discriminating sensor for side impacts, the combined system does function properly. Recent advances now permit electronic crash sensors to be mounted in the side as well as the front and rear crush zones.
An alternate use of the crush sensor such as the rod-in-tube sensor in side impacts is as a safing sensor. In this role, it merely determines that a crash is in progress and the main discriminating function is handled by the velocity sensing sensors such as disclosed in U.S. Pat. No. 05,231,253 (assigned to the current assignee). The rod-in-tube or coaxial cable crush velocity sensing crash sensors solve this side impact problem and thus applications include frontal, side and rear impacts, where in each case they enjoy significant advantages over all other crash sensing technologies. With respect to other prior art related to the certain embodiments of the invention, Peachey (U.S. Pat. No. 04,060,705) describes a pressure actuated continuous switch which designed to actuate about its entire circumference, i.e., in all directions. The switch of the embodiment in FIG. 1 of Peachey includes a central, inner conductor 1, an insulating thread 2 helically wound around the conductor 1 and an outer conductor 3, all housed within a sheath of insulating material 4. The switch in the embodiment of FIG. 2 includes a central, inner conductor 1, an insulating thread 2 helically wound around the conductor 1, a sheath of graphite-loaded plastic 5 surrounding the thread 2, an outer conductor 3 surrounding the sheath 5 and a sheath of insulating material 4 surrounding the outer conductor 3. The switch in these embodiments is actuated when pressure is applied to the switch so that the outer conductor (FIG. 1) or sheath 5 (FIG. 2) is deflected to cause it to make contact with the inner conductor 1 and thereby establish electrical contact between the inner and outer conductors 1,3, in the embodiment of FIG. 2 through the sheath 5. In view of the helical winding of the insulating thread 2 around the inner conductor 1, these switches can be actuated by bending at almost all locations (except for an impact into a location where the insulating material 2 is interposed between the conductors 1,3).
U.S. Pat. No. 02,437,969 to Paul describes a deformable switch 10 in the form of a tube that is actuatable at all circumferential points along its length. The tube includes a central coil of electrically conducting wire 12, a braided electrically conducting, metal tube 11 and insulating separators 13 spaced at discrete locations along the length of the switch 10 to support the tube 11 around the wire 12. The switch is actuatable at all circumferential locations along the length of the tube, except for the locations at which the insulating separators 13 are located. In use, when pressure is applied to the tube 11, it deforms at the location at which pressure is applied thereby coming into contact with the wire II and causing a circuit to close.
U.S. Pat. No. 05,322,323 to Ohno et al. describes to a collision sensing system for an airbag including collision sensors and acceleration sensors wherein deployment of the airbag is based on a signal from the collision sensors and an analysis of the output from the acceleration sensors.
U.S. Pat. No. 05,797,623 to Hubbard describes an allegedly unique side impact sensor based on a piezoelectric film. The sensor essentially measures the energy of impact providing the entire force applied to the film, which would not in general be the case. The velocity of the impacting vehicle can be determined again if the sensor absorbs the entire force and if the mass of the impacting object is known. Since neither of these can be assumed, the device will not provide a measurement of the impacting velocity and therefore at best can act as an impact-sensing switch with some discriminating capability.
The prior art crush zone mounted sensors therefore are either force sensing switches (Matsui) or piezoelectric film sensors (Hubbard) mounted in the forwardmost part of the crush zone, are velocity change sensors (ball-in-tube) mounted at the rear most edge of the CSZ or crush sensing switches also mounted at the rear most edge of the CSZ. Sensors mounted at the rear most edge of the CSZ by nature will trigger at the last possible moment when the airbag must deploy based on the seating position of the average male occupant. It is known that currently up to about 70% of vehicle occupants sit closer to the airbag than the average male and therefore such sensors trigger airbag deployment late for such occupants placing them at risk of being injured by the airbag. Heretofore, there are no velocity change sensors that are mounted in the forward part of the crush zone where the velocity change of the crash can be determined early in the crash and the airbag deployed early. There is thus a need for such a crash sensor.
5. Anticipatory Sensing
Although there has been a great deal of discussion on the use of anticipatory sensors for initiating restraint deployment, no practical systems have been developed other than those of the current assignee of this invention. The basic problem has been that an airbag should not be deployed unless the approaching object can be identified as a serious threat. The neural network systems developed by the current assignee is the first system capable of identifying such threatening objects.
6. Sensor Combinations
Up until the time that the first parent application was filed to this invention, the only use of sensor combinations was where a discriminating sensor was in series with a safing or arming sensor and where a crush zone mounted discriminating sensor was in parallel with a passenger compartment discriminating sensor where either one could initiate deployment of the restraint system.
7. Self-Contained Airbag Systems
Self-contained airbag systems contain all of the parts of the airbag system within a single package, in the case of mechanical implementations, and in the case of electrical or electronic systems, all parts except the primary source of electrical power and, in some cases, the diagnostic system. This includes the sensor, inflator and airbag. Potentially, these systems have significant cost and reliability advantages over conventional systems where the sensor(s), diagnostic and backup power supply are mounted separate from the airbag module. In mechanical implementations in particular, all of the wiring, the diagnostic system and backup power supply are eliminated. In spite of these advantages, self-contained airbag systems have only achieved limited acceptance for frontal impacts and have so far not been considered for side impacts.
The “all-mechanical” self-contained systems were the first to appear on the market for frontal impacts but have not been widely adopted partially due to their sensitivity to accelerations in the vertical and lateral directions. These cross-axis accelerations have been shown to seriously degrade the performance of the most common all mechanical design that is disclosed in Thuen, U.S. Pat. No. 04,580,810. Both frontal and side impact crashes frequently have severe cross-axis accelerations.
Additionally, all-mechanical self contained airbag systems, such as disclosed in the Thuen patent, require that the sensor be placed inside of the inflator which increases the strength requirements of the inflator walls and thus increases the size and weight of the system. One solution to this problem appears in Breed, U.S. Pat. No. 04,711,466, but has not been implemented. This patent discloses a method of initiating an inflator through the use of a percussion primer in combination with a stab primer and the placement of the sensor outside of the inflator. One disadvantage of this system is that a hole must still be placed in the inflator wall to accommodate the percussion primer that has its own housing. This hole weakens the wall of the inflator and also provides a potential path for gas to escape.
Another disadvantage in the Thuen system that makes it unusable for side impacts is that the arming system is sealed from the environment by an O-ring. This sealing method may perform satisfactorily when the system is mounted in the protected passenger compartment but it would not be satisfactory for side impact cases where the system would be mounted in the vehicle door where it can be subjected to water, salt, dirt, and other harsh environments.
Self-contained electrical systems have also not been widely used. When airbags are used for both the driver and the passenger, self-contained airbag systems require a separate sensor and diagnostic for each module. In contrast to mechanical systems, the electronic sensor and diagnostic systems used by most vehicle manufacturers are expensive. This duplication and associated cost required for electrical systems eliminates some of the advantages of the self-contained system.
Sensors located in the passenger compartment of a vehicle can catch most airbag-required crashes for frontal impacts, particularly if the occupants are wearing seatbelts. Also, if the teachings of this invention are practiced where an algorithm based on pattern recognition is used, then almost all frontal crash can be sensed in time in the passenger compartment. Mechanical sensors, however, are not capable of implementing such algorithms and thus researchers now believe that there are a significant number of crashes that cannot be sensed in time in the passenger compartment by mechanical sensors and that this will require the addition of another sensor mounted in the crush zone (see, for example, reference 5 below). If true, this will eventually eliminate the use of mechanical self-contained airbag systems for frontal impacts.
Some of these problems do not apply to side impacts mainly because side impact sensors must trigger in a very few milliseconds when there is no significant signal at any point in the vehicle except where the car is crushing or at locations rigidly attached to this crush zone. Each airbag system must be mounted in the crush zone and generally will have its own sensor. Self-contained airbag systems have heretofore not been used for occupant protection for side impacts, which is largely due to the misconception that side impact sensing requires the use of elongated switches as is discussed in detail in U.S. Pat. No. 05,231,253. These elongated side impact crush-sensing switches are not readily adaptable to the more compact self-contained designs. The realization that a moving mass sensor was the proper method for sensing side impacts has now led to the development of the side impact self-contained airbag system of this invention. The theory of sensing side impacts is included in the '253 patent referenced above.
In electromechanical and electronic self-contained modules, the backup power supply and diagnostic system can be mounted apart from the airbag system. If a wire is severed during a crash but before the airbag deploys, the system may lose its power and fail to deploy. This is more likely to happen in a side impact where the wires must travel inside of the door. For this reason, mechanical self-contained systems have a significant reliability advantage over conventional electrical or electronic systems for side impacts.
Finally, the space available for mounting airbag systems in the doors of vehicles is frequently severely limited making it desirable that the airbag module be as small as possible. Conventional gas generators use sodium azide as the gas generating propellant. This requires that the gas be cooled and extensively filtered to remove the sodium oxide, a toxic product of combustion. This is because the gas is exhausted into the passenger compartment where it can burn an occupant and be inhaled. If the gas is not permitted to enter the passenger compartment, the temperature of the gas can be higher and the products of combustion can contain toxic chemicals, such as carbon dioxide.
These and other problems associated with self-contained airbag systems and side impact sensors are solved by the invention disclosed herein.
8. Occupant Sensing
Automobiles equipped with airbags are well known in the prior art. In such airbag systems, the car crash is sensed and the airbags rapidly inflated thereby insuring the safety of an occupation in a car crash. Many lives have now been saved by such airbag systems. However, depending on the seated state of an occupant, there are cases where his or her life cannot be saved even by present airbag systems. For example, when a passenger is seated on the front passenger seat in a position other than a forward facing, normal state, e.g., when the passenger is out of position and near the deployment door of the airbag, there will be cases when the occupant will be seriously injured or even killed by the deployment of the airbag.
Also, sometimes a child seat is placed on the passenger seat in a rear facing position and there are cases where a child sitting in such a seat has been seriously injured or killed by the deployment of the airbag.
Furthermore, in the case of a vacant seat, there is no need to deploy an airbag, and in such a case, deploying the airbag is undesirable due to a high replacement cost and possible release of toxic gases into the passenger compartment. Nevertheless, most airbag systems will deploy the airbag in a vehicle crash even if the seat is unoccupied.
Thus, whereas thousands of lives have been saved by airbags, a large number of people have also been injured, some seriously, by the deploying airbag, and over 100 people have now been killed. Thus, significant improvements need to be made to airbag systems. As discussed in detail in U.S. Pat. No. 05,653,462, for a variety of reasons vehicle occupants may be too close to the airbag before it deploys and can be seriously injured or killed as a result of the deployment thereof. Also, a child in a rear facing child seat that is placed on the right front passenger seat is in danger of being seriously injured if the passenger airbag deploys. For these reasons and, as first publicly disclosed in Breed, D. S. “How Airbags Work” presented at the International Conference on Seatbelts and Airbags in 1993 in Canada, occupant position sensing and rear facing child seat detection systems are required in order to minimize the damages caused by deploying front and side airbags. It also may be required in order to minimize the damage caused by the deployment of other types of occupant protection and/or restraint devices that might be installed in the vehicle.
For these reasons, there has been proposed an occupant sensor system also known as a seated-state detecting unit such as disclosed in the following U.S. patents assigned to the current assignee of the present application: Breed et al. (U.S. Pat. No. 05,563,462); Breed et al. (U.S. Pat. No. 05,829,782); Breed et al. (U.S. Pat. No. 05,822,707): Breed et al. (U.S. Pat. No. 05,694,320); Breed et al. (U.S. Pat. No. 05,748,473); Varga et al. (U.S. Pat. No. 05,943,295); Breed et al. (U.S. Pat. No. 06,078,854); Breed et al. (U.S. Pat. No. 06,081,757); and Breed et al. (U.S. Pat. No. 06,242,701). Typically, in some of these designs, three or four sensors or sets of sensors are installed at three or four points in a vehicle for transmitting ultrasonic or electromagnetic waves toward the passenger or driver's seat and receiving the reflected waves. Using appropriate hardware and software, the approximate configuration of the occupancy of either the passenger or driver seat can be determined thereby identifying and categorizing the occupancy of the relevant seat.
9. Controlling Airbag Inflation
There are many ways of controlling the inflation of the airbag and several are now under development by the inflator companies, the current assignee and others. One way is to divide the airbag into different charges and to initiate these charges independently as a function of time to control the airbag inflation. An alternative is to always generate the maximum amount of gas but to control the amount going into the airbag, dumping the rest into the atmosphere. A third way is to put all of the gas into the airbag but control the outflow of the gas from the airbag through a variable vent valve. For the purposes herein, all controllable apparatus for varying the gas flow into and/or out of the airbag over time will be considered as a gas control module whether the decision is made at the time of initial airbag deployment, at one or more discrete times later or continuously during the crash event.
10. Diagnostics
Every automobile driver fears that his or her vehicle will breakdown at some unfortunate time, e.g., when he or she is traveling at night, during rush hour, or on a long trip away from home. To help alleviate that fear, certain luxury automobile manufacturers provide roadside service in the event of a breakdown. Nevertheless, unless the vehicle is equipped with OnStar® or an equivalent service, the vehicle driver must still be able to get to a telephone to call for service. It is also a fact that many people purchase a new automobile out of fear of a breakdown with their current vehicle. This invention is also concerned with preventing breakdowns and with minimizing maintenance costs by predicting component failure that would lead to such a breakdown before it occurs.
When a vehicle component begins to fail, the repair cost is frequently minimal if the impending failure of the component is caught early, but increases as the repair is delayed. Sometimes if a component in need of repair is not caught in a timely manner, the component, and particularly the impending failure thereof, can cause other components of the vehicle to deteriorate. One example is where the water pump fails gradually until the vehicle overheats and blows a head gasket. It is desirable, therefore, to determine that a vehicle component is about to fail as early as possible so as to minimize the probability of a breakdown and the resulting repair costs.
There are various gages on an automobile which alert the driver to various vehicle problems. For example, if the oil pressure drops below some predetermined level, the driver is warned to stop his vehicle immediately. Similarly, if the coolant temperature exceeds some predetermined value, the driver is also warned to take immediate corrective action. In these cases, the warning often comes too late as most vehicle gages alert the driver after he or she can conveniently solve the problem. Thus, what is needed is a component failure warning system that alerts the driver to the impending failure of a component sufficiently in advance of the time when the problem gets to a catastrophic point.
Some astute drivers can sense changes in the performance of their vehicle and correctly diagnose that a problem with a component is about to occur. Other drivers can sense that their vehicle is performing differently but they don't know why or when a component will fail or how serious that failure will be, or possibly even what specific component is the cause of the difference in performance. The invention disclosed herein will, in most cases, solve this problem by predicting component failures in time to permit maintenance and thus prevent vehicle breakdowns.
Presently, automobile sensors in use are based on specific predetermined or set levels, such as the coolant temperature or oil pressure, whereby an increase above the set level or a decrease below the set level will activate the sensor, rather than being based on changes in this level over time. The rate at which coolant heats up, for example, can be an important clue that some component in the cooling system is about to fail. There are no systems currently on automobiles to monitor the numerous vehicle components over time and to compare component performance with normal performance. Nowhere in the vehicle is the vibration signal of a normally operating front wheel stored, for example, or for that matter, any normal signal from any other vehicle component. Additionally, there is no system currently existing on a vehicle to look for erratic behavior of a vehicle component and to warn the driver or the dealer that a component is misbehaving and is therefore likely to fail in the very near future.
Sometimes, when a component fails, a catastrophic accident results. In the Firestone tire case, for example, over 100 people were killed when a tire of a Ford Explorer blew out which caused the Ford Explorer to rollover. Similarly, other component failures can lead to loss of control of the vehicle and a subsequent accident. It is thus very important to accurately forecast that such an event will take place but furthermore, for those cases where the event takes place suddenly without warning, it is also important to diagnose the state of the entire vehicle, which in some cases can lead to automatic corrective action to prevent unstable vehicle motion or rollovers resulting in an accident. Finally, an accurate diagnostic system for the entire vehicle can determine much more accurately the severity of an automobile crash once it has begun by knowing where the accident is taking place on the vehicle (e.g., the part of or location on the vehicle which is being impacted by an object) and what is colliding with the vehicle based on a knowledge of the force deflection characteristics of the vehicle at that location. Therefore, in addition to a component diagnostic, the teachings of this invention also provide a diagnostic system for the entire vehicle prior to and during accidents. In particular, this invention is concerned with the simultaneous monitoring of multiple sensors on the vehicle so that the best possible determination of the state of the vehicle can be determined. Current crash sensors operate independently or at most one sensor may influence the threshold at which another sensor triggers a deployable restraint. In the teachings of this invention, two or more sensors, frequently accelerometers, are monitored simultaneously and the combination of the outputs of these multiple sensors are analyzed continuously in making the crash severity analysis.
11. Smart Airbags
Since there is insufficient information in the acceleration data, as measured in the passenger compartment, to sense all crashes and since some of the failure modes of published single point sensor algorithms can be easily demonstrated using the techniques of crash and velocity scaling described in the above-referenced technical papers, and moreover since the process by which engineers develop algorithms is generally based on trial and error, pattern recognition techniques such as neural network should be able to be used to create an algorithm based on training the system on a large number of crash and non-crash events which, although not perfect, will be superior to all others. This in fact has proved to be true and is the subject the invention disclosed in U.S. Pat. No. 05,684,701. That invention is based on the ability of neural networks to forecast, based on the first part of the crash pulse, that the crash will be of a severity which requires that an airbag be deployed.
As will be discussed in greater detail below, an improvement on that invention, which is a subject of the instant invention, carries this process further by using a neural network pattern recognition system to forecast the velocity change of the crash over time so that the inflation and/or deflation of the airbag, and optionally the tensioning of the seatbelt, can be optimized. This invention further contemplates the addition of the pattern recognition occupant position and velocity determination means disclosed in U.S. Ser Nos. 05,829,782, 06,343,810 and U.S. RE 37,260. Finally, the addition of the weight of the occupant is contemplated to provide a measure of the occupant's inertia or momentum as an input to the system. The combination of these systems in various forms can be called “smart airbags” or “smart restraints” which will be used as equivalents herein. In a preferred implementation, the crash severity is not explicitly forecasted but rather, the value of a control parameter used to control the flows of inflator gas into and/or out of the airbag is forecasted.
Smart airbags can take several forms which can be roughly categorized into four evolutionary stages, which will hereinafter be referred to as Phase 1 (2, 3 or 4) Smart Airbags, as follows:    1) Occupant sensors such as the disclosed in the U.S. patent applications cross-referenced above use various technologies to turn off the airbag where there is a rear-facing child seat present or if either the driver or passenger is out-of-position, i.e., in a position in which he/she is more likely to be injured by the airbag than from the accident.    2) Occupant sensors will be used along with variable inflation and/or deflation rate airbags to adjust the inflation/deflation rate to match the occupant first as to his/her position and then to his/her morphology. The occupant sensors disclosed in the cross-referenced patents and patent applications will also handle this with the possible addition of an occupant weighing system. One particular weight measuring system which makes use of strain gages mounted onto the seat supporting structure is disclosed in U.S. Pat. No. 05,748,473, another that makes use of a fluid filled bladder is disclosed in U.S. Pat. No. 06,442,504 and still another uses a mat in the seat to measure the pressure distribution of the occupant as disclosed in U.S Ser. No. 06,412,357. At the end of this phase, little more can be done with occupant measurement or characterization systems.    3) The next improvement, and a subject of the instant invention, is to use a pattern recognition system such as neural networks as the basis of a crash sensor system not only to determine if the airbag should be deployed but also to predict the crash severity from the pattern of the initial portion of the crash pulse. Additionally, the crash pulse will continue to be monitored even after the decision has been made to deploy the airbag to see if the initial assumption of the crash type based on the pattern up to the deployment decision was correct. If the pattern changes indicating a different crash type, the flow rate to the airbag can be altered on the fly, i.e., substantially instantaneously. This crash sensor system can consist of a single electronic accelerometer based passenger compartment sensor, a multiple sensor system that also includes either electronic or mechanical crush zone mounted sensors and in the most sophisticated cases, the passenger compartment sensor is replaced by an inertial measurement unit (IMU). Such an IMU can consist of up to three accelerometers and up to three gyroscopes, usually based on MEMS technologies. It can also be coupled to the vehicle navigation system whereby the accuracy of the IMU can be enhanced through a technique such as a Kalman filter and a GPS or DGPS system or other absolute positioning system.    4). Finally, anticipatory sensing, using radar, laser radar, acoustics, or cameras, and also using pattern recognition techniques such as neural networks will be used to identify the crash before it takes place and select the deployment characteristics of the airbag to match the anticipated crash with the occupant size and position. Such an anticipatory sensor is described in U.S. Pat. No. 06,343,810.
Any of these phases can be combined with various methods of controlling the pretensioning, retraction and/or energy dissipation characteristics of the seatbelt. Although a primary focus of this invention is the control of the flows of gas into and out of the airbag, it is to be recognized that control of the seatbelt, or any other restraint, can also benefit from this invention and that the condition of the seatbelt can be valuable input information into the pattern recognition system.
The smart airbag problem is complex and difficult to solve by ordinary mathematical methods. Looking first at the influence of the crash pulse, the variation of crash pulses in the real world is vast and quite different from the typical crashes run by the automobile industry as reported in the technical papers referenced herein. It is one problem to predict that a crash has a severity level requiring the deployment of an airbag. It is quite a different problem to predict exactly what the velocity versus time function will be and then to adjust the airbag inflation/deflation control system to make sure that just the proper amount of gas is in the airbag at all times even without considering the influence of the occupant. To also simultaneously consider the influence of occupant size, weight, position and/or velocity, renders this problem for all practical purposes unsolvable by conventional methods.
On the other hand, if a pattern recognition system such as a neural network is used and trained on a large variety of crash acceleration segments, as described in U.S. Pat. No. 05,684,701, and a setting for the inflation/deflation control system is specified for each segment, then the problem can be solved. Furthermore, inputs from the occupant position and occupant weight sensors can also be included. The result will be a training set for the neural network involving many millions, and perhaps tens of millions, of data sets or vectors as every combination of occupancy characteristics and acceleration segment is considered. Fortunately, the occupancy data can be acquired independently and is currently being done for solving the out-of-position problem of Phase 1 smart airbags. The crash data is available in abundance and more can be created using the crash and velocity scaling techniques described in the above-referenced papers. The training using combinations of the two data sets, which must also take into account occupant motion which is not adequately represented in the occupancy data, can then be done by computer. Even the computer training process is significant to tax current PC capabilities, and in some cases, the use of a super-computer may be warranted.
12. Definitions
An IMU, or Inertial Measurement Unit, is usually a self-contained device that usually has three orthogonal accelerometers and three gyroscopes. In some cases, a smaller number can be used.
“Pattern recognition” as used herein will generally mean any system which processes a signal that is generated by an object (e.g., representative of a pattern of returned or received impulses, waves or other physical property specific to and/or characteristic of and/or representative of that object) or is modified by interacting with an object, in order to determine to which one of a set of classes that the object belongs. Such a system might determine only that the object is or is not a member of one specified class, or it might attempt to assign the object to one of a larger set of specified classes, or find that it is not a member of any of the classes in the set. The object can also be a vehicle with an accelerometer that generates a signal based on the deceleration of the vehicle. Such a system might determine only that the object is or is not a member of one specified class (e.g., airbag-required crashes), or it might attempt to assign the object to one of a larger set of specified classes, or find that it is not a member of any of the classes in the set. One such class might consist of vehicles undergoing a crash of a certain severity into a pole. The signals processed are generally a series of electrical signals coming from transducers that are sensitive to acoustic (ultrasonic) or electromagnetic radiation (e.g., visible light, infrared radiation, capacitance or electric and/or magnetic fields), although other sources of information are frequently included. Pattern recognition systems generally involve the creation of a set of rules that permit the pattern to be recognized. These rules can be created by fuzzy logic systems, statistical correlations, or through sensor fusion methodologies as well as by trained pattern recognition systems such as neural networks, combination neural networks, cellular neural networks or support vector machines.
A trainable or a trained pattern recognition system as used herein generally means a pattern recognition system that is taught to recognize various patterns constituted within the signals by subjecting the system to a variety of examples. The most successful such system is the neural network used either singly or as a combination of neural networks. Thus, to generate the pattern recognition algorithm, test data is first obtained which constitutes a plurality of sets of returned waves, or wave patterns, or other information radiated or obtained from an object (or from the space in which the object will be situated in the passenger compartment, i.e., the space above the seat) and an indication of the identity of that object. A number of different objects, optionally in different positions, are tested to obtain the unique patterns from each object. As such, the algorithm is generated, and stored in a computer processor, and which can later be applied to provide the identity of an object based on the wave pattern being received during use by a receiver connected to the processor and other information. For the purposes here, the identity of an object sometimes applies to not only the object itself but also to its location and/or orientation in the passenger compartment. For example, a rear-facing child seat is a different object than a forward-facing child seat and an out-of-position adult can be a different object than a normally-seated adult. Not all pattern recognition systems are trained systems and not all trained systems are neural networks. Other pattern recognition systems are based on fuzzy logic, sensor fusion, Kalman filters, correlation as well as linear and non-linear regression. Still other pattern recognition systems are hybrids of more than one system such as neural-fuzzy systems.
The use of pattern recognition, or more particularly how it is used, is important to the instant invention. In the above-cited prior art, except in that assigned to the current assignee, pattern recognition which is based on training, as exemplified through the use of neural networks, is not mentioned for use in monitoring the interior passenger compartment or exterior environments of the vehicle in all of the aspects of the invention disclosed herein. Thus, the methods used to adapt such systems to a vehicle are also not mentioned.
A pattern recognition algorithm will thus generally mean an algorithm applying or obtained using any type of pattern recognition system, e.g., a neural network, sensor fusion, fuzzy logic, etc.
To “identify” as used herein will generally mean to determine that the object belongs to a particular set or class. The class may be one containing, for example, all rear facing child seats, one containing all human occupants, or all human occupants not sitting in a rear facing child seat, or all humans in a certain height or weight range depending on the purpose of the system. In the case where a particular person is to be recognized, the set or class will contain only a single element, i.e., the person to be recognized. The class may also be one containing all frontal impact airbag-desired crashes into a pole at 20 mph, one containing all events where the airbag is not required, or one containing all events requiring a triggering of both stages of a dual stage gas generator with a 15 millisecond delay between the triggering of the first and second stages.
To “ascertain the identity of” as used herein with reference to an object will generally mean to determine the type or nature of the object (obtain information as to what the object is), i.e., that the object is an adult, an occupied rear-facing child seat, an occupied front-facing child seat, an unoccupied rear-facing child seat, an unoccupied front-facing child seat, a child, a dog, a bag of groceries, a car, a truck, a tree, a pedestrian, a deer etc.
An “object” in a vehicle or an “occupying item” of a seat may be a living occupant such as a human or a dog, another living organism such as a plant, or an inanimate object such as a box or bag of groceries or an empty child seat.
A “rear seat” of a vehicle as used herein will generally mean any seat behind the front seat on which a driver sits. Thus, in minivans or other large vehicles where there are more than two rows of seats, each row of seats behind the driver is considered a rear seat and thus there may be more than one “rear seat” in such vehicles. The space behind the front seat includes any number of such rear seats as well as any trunk spaces or other rear areas such as are present in station wagons.
An “optical image” will generally mean any type of image obtained using electromagnetic radiation including visual, infrared and radar radiation.
In the description herein on anticipatory sensing, the term “approaching” when used in connection with the mention of an object or vehicle approaching another will usually mean the relative motion of the object toward the vehicle having the anticipatory sensor system. Thus, in a side impact with a tree, the tree will be considered as approaching the side of the vehicle and impacting the vehicle. In other words, the coordinate system used in general will be a coordinate system residing in the target vehicle. The “target” vehicle is the vehicle that is being impacted. This convention permits a general description to cover all of the cases such as where (i) a moving vehicle impacts into the side of a stationary vehicle, (ii) where both vehicles are moving when they impact, or (iii) where a vehicle is moving sideways into a stationary vehicle, tree or wall.
“Out-of-position” as used for an occupant will generally mean that the occupant, either the driver or a passenger, is sufficiently close to an occupant protection apparatus (airbag) prior to deployment that he or she is likely to be more seriously injured by the deployment event itself than by the accident. It may also mean that the occupant is not positioned appropriately in order to attain the beneficial, restraining effects of the deployment of the airbag. As for the occupant being too close to the airbag, this typically occurs when the occupant's head or chest is closer than some distance such as about 5 inches from the deployment door of the airbag module. The actual distance where airbag deployment should be suppressed depends on the design of the airbag module and is typically farther for the passenger airbag than for the driver airbag.
“Transducer” or “transceiver” as used herein will generally mean the combination of a transmitter and a receiver. In come cases, the same device will serve both as the transmitter and receiver while in others two separate devices adjacent to each other will be used. In some cases, a transmitter is not used and in such cases, transducer will mean only a receiver. Transducers include, for example, capacitive, inductive, ultrasonic, electromagnetic (antenna, CCD, CMOS arrays), electric field, weight measuring or sensing devices. In some cases, a transducer may comprise two parts such as the plates of a capacitor or the antennas of an electric field sensor. Sometimes, one antenna or plate will communicate with several other antennas or plates and thus for the purposes herein, a transducer will be broadly defined to refer, in most cases, to any one of the plates of a capacitor or antennas of a field sensor and in some other cases, a pair of such plates or antennas will comprise a transducer as determined by the context in which the term is used.
For the purposes herein, a “neural network” is defined to include all such learning systems including cellular neural networks, support vector machines and other kernel-based learning systems and methods, cellular automata and all other pattern recognition methods and systems that learn. A “combination neural network” as used herein will generally apply to any combination of two or more neural networks as most broadly defined that are either connected together or that analyze all or a portion of the input data. Typically, it is a system wherein the data to be processed is separated into discrete values which are then operated on and combined in at least a two stage process and where the operation performed on the data at each stage is, in general, different for each discrete value and where the operation performed is at least determined through a training process. It includes ensemble, modular, cellular neural networks, among others, and support vector machines and combination Neural Networks.
A “sensor” as used herein is the combination of two transducers (a transmitter and a receiver) or one transducer which can both transmit and receive. The headliner is the trim which provides the interior surface to the roof of the vehicle and the A-pillar is the roof-supporting member which is on either side of the windshield and on which the front doors are hinged.
A “sensor system” includes any of the sensors listed above in the definition of “sensor” as well as any type of component or assembly of components that detect, sense or measure something.
An “occupant protection apparatus” is any device, apparatus, system or component which is actuatable or deployable or includes a component which is actuatable or deployable for the purpose of attempting to reduce injury to the occupant in the event of a crash, rollover or other potential injurious event involving a vehicle
An “occupant restraint device” includes any type of device that is deployable in the event of a crash involving the vehicle for the purpose of protecting an occupant from the effects of the crash and/or minimizing the potential injury to the occupant. Occupant restraint devices thus include frontal airbags, side airbags, seatbelt tensioners, nets, knee bolsters, side curtain airbags, externally deployable airbags and the like.
A diagnosis of the “state of the vehicle” means a diagnosis of the condition of the vehicle with respect to its stability and proper running and operating condition. Thus, the state of the vehicle could be normal when the vehicle is operating properly on a highway or abnormal when, for example, the vehicle is experiencing excessive angular inclination (e.g., two wheels are off the ground and the vehicle is about to rollover), the vehicle is experiencing a crash, the vehicle is skidding, and other similar situations. A diagnosis of the state of the vehicle could also be an indication that one of the parts of the vehicle, e.g., a component, system or subsystem, is operating abnormally.
A “part” of the vehicle includes any component, sensor, system or subsystem of the vehicle such as the steering system, braking system, throttle system, navigation system, airbag system , seatbelt retractor, air bag inflation valve, air bag inflation controller and airbag vent valve, as well as those listed below in the definitions of “component” and “sensor”.
The crush zone is that portion of the vehicle that has crushed at the time that the crash sensor must trigger deployment of the restraint system.
The term “airbag” has been used to mean all deployable passive passenger protective devices including airbags, seatbelts with pretensioners and deployable nets.